AI Engineer

AI Engineer

Full-Time 74000 - 81000 £ / year (est.) No working from home possible
Reward Gateway

At a Glance

  • Tasks: Create innovative AI solutions and enhance internal tools for a better user experience.
  • Company: Join a global leader in employee engagement and benefits.
  • Benefits: Competitive salary, inclusive culture, and opportunities for personal growth.
  • Other info: Inclusive recruitment process and commitment to diversity and innovation.
  • Why this job: Make a real impact with cutting-edge AI technology in a supportive environment.
  • Qualifications: Experience in AI solutions, strong Python skills, and cloud engineering knowledge.

The predicted salary is between 74000 - 81000 £ per year.

Reward Gateway | Edenred is a global leader in benefits and employee engagement. We help businesses attract, engage, and retain top talent through strategic rewards, recognition, and well-being solutions. Guided by our shared missions of ‘Making the World a Better Place to Work’ and ‘Enriching Connections, For Good’, we are committed to transforming workplaces and improving people’s daily lives.

As we continue to expand our business, we have an opportunity for a hands-on AI Engineer who is excited about turning real-world challenges into smart, scalable solutions. You will work with the latest third-party AI services, build streamlined workflows and craft high-impact prompts that boost our internal tools, speed up developer productivity and elevate the customer experience. You will work closely with Product, Operations, and Engineering teams to turn ideas into practical solutions and contribute to improvements across the platform.

Key Responsibilities
  • Build and deliver production-ready AI and Generative AI solutions using LLMs, RAG architectures, agents, and responsible AI practices.
  • Use AI coding assistants such as Cursor, GitHub Copilot, and Claude Code to accelerate development while maintaining ownership of outcomes and documenting best practices and repeatable patterns.
  • Manage cloud infrastructure and platform operations, including AWS, Kubernetes, CI/CD pipelines, Terraform, monitoring, performance optimisation, and cost control.
  • Design, develop, and maintain backend services in Python, and contribute to React, TypeScript, and PHP codebases when required.
  • Lead evaluation and iteration cycles, including defining and tracking offline and online metrics, running A/B tests, meeting latency and cost targets, implementing human-in-the-loop validation, and ensuring robust observability.
  • Implement and maintain retrieval pipelines using embeddings, vector databases, hybrid search methods, and effective chunking strategies.
  • Collaborate closely with Product using a working-backwards approach, producing technical designs, breaking down work, and delivering iteratively.
  • Improve internal AI development tooling, including shared libraries, SDKs, and reference implementations for RAG, tracing, prompt management, and evaluation.
  • Contribute to internal enablement and capability-building activities across the organisation.
  • Partner with Security, Legal, and Data teams to define AI policies, review risks, and ensure privacy, PII protection, and regulatory compliance.
  • Mentor peers, conduct code reviews, and share knowledge to elevate engineering standards across the organisation.
Skills, Knowledge and Expertise
  • Proven experience in shipping production-grade AI solutions.
  • Applied AI expertise across LLMs, RAG, agentic workflows, prompt engineering, embeddings, vector databases, hybrid search techniques, and effective chunking strategies.
  • Strong Python as a primary language, with solid testing practices and CI/CD experience; able to contribute when needed in React, TypeScript, and PHP or Node.js.
  • Cloud and platform engineering skills, including AWS, Kubernetes, Docker, infrastructure as code, and modern observability tooling.
  • Hands-on experience with leading LLM providers such as Anthropic, Claude and OpenAI, with the ability to evaluate additional model providers and approaches.
  • Familiarity with LLM tooling ecosystems such as LangChain or LlamaIndex, agentic AI frameworks, vector stores, tracing and logging tools, prompt management platforms, and evaluation frameworks.
  • Strong data engineering capabilities, including dataset creation and validation, ETL development, SQL schema design, and the definition and tracking of meaningful product and model metrics.
  • Solid understanding of ML fundamentals and experimentation, including metric design, error analysis, model selection, and performance tuning.
  • A strong security and governance mindset, with the ability to communicate clearly with both technical and non-technical audiences, and a high level of ownership from discovery through production and iterative improvement.
The Interview Process
  • Online interview with the Talent Partner and the Director of AI Engineering.
  • Technical interview with Director of AI Engineering, VP of Product Engineering, and VP of Product.

At Reward Gateway | Edenred we are committed to ensuring an inclusive and accessible recruitment process for all candidates. If you have any specific requirements or need reasonable adjustments at any stage of the recruitment journey, please let your Talent Acquisition Partner know. Your needs are important to us, and we want to ensure an equitable experience for every candidate.

Be comfortable. Be you. We want every employee to feel comfortable bringing their passion, creativity, and individuality to work. We value all cultures, backgrounds, and experiences, because we believe diversity drives innovation and makes us stronger. Our approach to hiring and building teams is about more than filling roles - it’s about creating an environment where everyone can thrive, feel supported, and contribute to our mission of making the world a better place to work.

AI Engineer employer: Reward Gateway

At Reward Gateway | Edenred, we pride ourselves on being an exceptional employer that fosters a vibrant and inclusive work culture in the heart of London. Our commitment to employee growth is evident through our focus on mentorship, collaboration, and continuous learning, ensuring that every team member can thrive while contributing to meaningful projects that enhance workplace well-being. With competitive compensation and a mission-driven approach, we empower our employees to make a positive impact, both within the company and in the wider community.

Reward Gateway

Contact Details:

Reward Gateway Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI Engineer

Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.

Tip Number 2

Prepare for those interviews! Research the company, understand their products, and be ready to discuss how your skills align with their needs. Practise common interview questions and have your own questions ready to show your interest.

Tip Number 3

Showcase your projects! Whether it's through a portfolio or GitHub, let your work speak for itself. Highlight any AI solutions you've built or contributed to, especially those that demonstrate your problem-solving skills.

Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at Reward Gateway | Edenred.

We think you need these skills to ace AI Engineer

AI and Generative AI solutions
LLMs (Large Language Models)
RAG architectures
Python programming
React
TypeScript
PHP

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the AI Engineer role. Highlight your experience with LLMs, RAG architectures, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for AI and how you can contribute to our mission of making the world a better place to work. Be genuine and let your personality come through.

Showcase Your Projects:If you've worked on any AI projects, make sure to include them in your application. Whether it's a personal project or something from your previous job, we love seeing real-world applications of your skills!

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're serious about joining our team!

How to prepare for a job interview at Reward Gateway

Know Your AI Stuff

Make sure you brush up on your knowledge of LLMs, RAG architectures, and prompt engineering. Be ready to discuss your hands-on experience with these technologies and how you've applied them in real-world scenarios.

Showcase Your Coding Skills

Prepare to demonstrate your Python prowess, especially in building production-grade AI solutions. You might be asked to solve coding challenges or discuss your approach to CI/CD practices, so have some examples ready.

Understand the Company’s Mission

Familiarise yourself with Reward Gateway | Edenred's mission of 'Making the World a Better Place to Work'. Think about how your skills can contribute to this goal and be prepared to share your thoughts during the interview.

Ask Insightful Questions

Prepare thoughtful questions for your interviewers about their AI initiatives and team dynamics. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values.